Impartial Schedule Targeted Nurse Scheduling Problems and Genetic Algorithm Based Methods
Date Issued
2010
Date
2010
Author(s)
Wu, Wei-Ting
Abstract
Nurse scheduling problem is a more specific problem comparing with the general employee scheduling problem. Generally, in our survey, nurse scheduling is solved manually by the head nurse due to the consideration of many conflict restrictions. However sometimes errors and time cost took places in the manually scheduling mode. Therefore, in order to increase the efficiency and provide a time-saving method to solve the nurse scheduling problem, this research establish two nurse scheduling modes - The Package Shift mode and Non-Package Shift mode.
The Package Shift mode is restricted to that the nurse only can take one type shift throughout one month. For example, once the Package Shift mode is adopted, the nurse is on night shift throughout this month, if starting on night shift. Contrary to the Package Shift mode, the Non-Package Shift mode is without this restriction.
In Taiwan, the head nurse will take the historical information about the nurses, such as nurse rank, accrued/owed leave and the number of furlough, in order to determine nurse requested leave priorities and carrying on nurse scheduling problem. On the other hand, the Benchmark problems of foreign hospitals belong to Non-Package Shift mode.
In order to solve the nurse scheduling problem automatically rather than manually, this research provide a huristic algorithm which is based on genetic algorithm and an automation software package is provided to solve nurse scheduling problem under Package Shift mode and Non-Package Shift mode.
Under Package Shift mode, for the sake of impartial of principle, historical data are utilized, such as the amount of leaves and the amount of shifts. Under Non-Package Shift mode, the Belgian hospital BCV range of issues are utilized to study the scheduling problem, in which, the Questions in the implementation of Various types of problem-specific GA program must be determined in first. Genetic algorithm model optimizes a number of sub-goals and guides the results toward the violation of constraint scheduling to minimize the number of the direction of evolution.
Compare to literatures, our result shows that this research perform much more effective and better on solving benchmark problem. Moreover, the numerical examples show that our proposed method can be an alternative of manual nurse scheduling, furthermore, applicable effectively on nurse scheduling under both Package Shift mode and Non-Package Shift mode.
Subjects
nurse scheduling problems
impartial
Package Shift
Non-Package Shift
genetic algorithms
SDGs
Type
thesis
File(s)![Thumbnail Image]()
Loading...
Name
ntu-99-R97546024-1.pdf
Size
23.53 KB
Format
Adobe PDF
Checksum
(MD5):2bdd51ad61680ddd7dff46f0bb3b85c6